(self)
| 111 | self.assertEqual(len(np.unique(encoded)), channels) |
| 112 | |
| 113 | def testEncodePrecomputed(self): |
| 114 | channels = 256 |
| 115 | number_of_samples = 10 |
| 116 | x = np.array([-1.0, 1.0, 0.6, -0.25, 0.01, |
| 117 | 0.33, -0.9999, 0.42, 0.1, -0.45]).astype(np.float32) |
| 118 | encoded_manual = np.array([0, 255, 243, 32, 157, |
| 119 | 230, 0, 235, 203, 18]).astype(np.int32) |
| 120 | |
| 121 | with self.test_session() as sess: |
| 122 | encoded = sess.run(mu_law_encode(x, channels)) |
| 123 | |
| 124 | self.assertAllEqual(encoded_manual, encoded) |
| 125 | |
| 126 | def testEncodeUniformRandomNoise(self): |
| 127 | np.random.seed(42) # For repeatability of test. |
nothing calls this directly
no test coverage detected